Recent headlines warn of cooling tech job postings and decrease beginning salaries, and tales are rife with fears that synthetic intelligence, or AI, will remove entry-level roles.
For college students contemplating a level in computer science or software program engineering, the information can sound discouraging.
Computer scientists in the Ira A. Fulton Schools of Engineering at Arizona State University say the actuality is extra nuanced, complicated and hopeful.
They level out that though instruments and platforms evolve, the core expertise of computer science stay helpful throughout industries. Those foundations have already survived main technological shifts, turning into extra important as industries tailored to new challenges.
Here they clarify extra about what to know when it comes to the way forward for AI and jobs.
Meet the specialists:
Ross Maciejewski
Ross Maciejewski, a professor of computer science and engineering and director of the School of Computing and Augmented Intelligence, a part of the Fulton Schools, leads one in every of the nation’s largest computer science applications and is internationally acknowledged for analysis in information visualization for homeland safety, public well being, social media and regulation enforcement.
Nadya Bliss
Nadya Bliss, government director of ASU’s Global Security Initiative, a Fulton Schools computer science and engineering professor of apply, and chair of the Computing Community Consortium, a part of the Computing Research Association, or CRA, is a number one computer scientist whose work advances nationwide safety and accountable innovation at the intersection of expertise and society.
Srividya Bansal
Srividya Bansal, an affiliate professor and program chair of software program engineering in the Fulton Schools, researches semantics-based approaches for large information integration and information networks whereas main efforts to put together industry-ready graduates by progressive hands-on curricula.
Q&A
Question: Is AI eliminating computer science jobs?
Maciejewski: Current reports don’t present a sweeping “AI effect.” Some research counsel at this time’s slowdown could possibly be the results of post-pandemic over-hiring. What’s undoubtedly taking place is a shift in how jobs are done. AI copilots can draft code, however that makes high quality assurance, integration and techniques pondering extra essential. Students who grasp these fundamentals can thrive.
Bliss: Computer science foundations, together with skills like problem-solving, abstraction and algorithmic pondering, don’t exit of fashion. Programming languages change, however core expertise endure. My mantra is easy: Do extra math. It makes you exact about assumptions and limitations, which is essential in an AI-driven world.
Bansal: In software program engineering, most effort is already in testing, debugging and upkeep. As Ross famous, AI can generate starter code, however college students should nonetheless validate, combine and safe it. Critical pondering and deep technical information are extra essential than ever.
Q: What historic patterns ought to college students bear in mind?
Maciejewski: Tech hiring has typically been quite cyclical. The early ’90s, the 2001 dot-com crash and the 2008 recession all introduced contractions, however the area rebounded with new platforms and alternatives. Students coming into faculty at this time will probably graduate right into a market that has absorbed AI extra thoughtfully, with a continued demand for engineers who can design and scale reliable techniques.
Bliss: Each main wave of expertise, from parallel computing to web commerce, reshaped the job market, however as an alternative of eliminating roles, it created new and totally different ones. With each enlargement, extra fields grew to become dependent on computer science experience, multiplying alternatives quite than decreasing them.
Bansal: We’ve seen related cycles with software program instruments. In the Eighties, it was reusable code libraries, then open-source frameworks and later built-in improvement environments that eased syntax and debugging. Each time, folks fearful jobs may disappear. Instead, productiveness elevated, and engineers moved on to sort out larger, extra complicated tasks, like net and cellular apps in the 2000s. AI is the subsequent wave in that very same sample. But it doesn’t remove the want for software program engineers. It pushes them to larger ranges of problem-solving.
Every {industry} is now a tech {industry}. No matter the place you go, corporations want individuals who can design, safe and preserve complicated computer techniques.
Ross Maciejewski, professor of computer science and engineering
Q: Where is job demand strongest proper now?
Maciejewski: Students with AI expertise are in demand, however shortages are additionally acute in cybersecurity and microelectronics. Globally, tens of millions extra cybersecurity professionals are wanted, and the U.S. semiconductor {industry} alone could require almost half 1,000,000 further employees by 2030. In the School of Computing and Augmented Intelligence, each undergraduate takes a cybersecurity course, and we provide concentrations to put together computer science college students for these roles.
Bliss: In ASU’s Global Security Initiative, we’re additionally making use of AI in mission-critical settings like protection and infrastructure. That’s the place college students be taught each functionality and duty: how AI may also help, the place it could actually fail and how to design round its limitations.
Q: How is ASU making ready college students for an AI-enabled future?
Maciejewski: ASU ranks amongst the top programs nationally in AI schooling. Students take programs in robotics, machine studying and autonomous techniques, however they’ll additionally acquire utilized expertise by internships and analysis that join AI to real-world challenges. The School of Computing and Augmented Intelligence can also be the residence of worldwide acknowledged school members similar to information mining trailblazer Huan Liu and Subbarao Kambhampati, a previous president of the Association for the Advancement of Artificial Intelligence and winner of the group’s 2025 Patrick Henry Winston Outstanding Educator Award. We consider college students have an actual alternative to have interaction with AI thought leaders right here in the faculty.
Bansal: In software program engineering, we focus on sturdy core expertise like techniques design, collaboration and resilience. Our capstone program is very highly effective. Industry sponsors convey actual issues, and college students carry tasks from necessities by design, coding and testing. Increasingly, these tasks are AI-enabled, involving advice engines, pure language processing or predictive analytics.
That means college students apply treating AI as a device, not a substitute. They be taught to use it for code scaffolding or testing, but additionally to critique outputs, debug errors and combine outcomes into bigger techniques. Employers inform us this fluency, the means to use AI whereas sustaining engineering rigor, is strictly what they want.
Bliss: That aligns with the outcomes of the most up-to-date Practitioner-to-Professor Survey from the CRA, the place we requested {industry} specialists to inform us what they have been seeing out in the office. The suggestions emphasised broad-based AI literacy, lifelong studying and cross-sector collaboration. ASU is constructed for that method.
Q: What expertise matter most to employers?
Bliss: Problem-solving, techniques pondering, experimentation and communication. Programming languages change, however fundamentals don’t. Employers additionally need teamwork, good smooth expertise and adaptability. These are issues that may matter much more once you’re working alongside AI.
Maciejewski: That’s why we encourage college students to transcend the classroom. Through research programs, service work and interdisciplinary projects, they apply management and collaboration. Employers more and more ask, “What have you built? How did you work on a team? How did you test your system?”
Bansal: Capstone tasks put together college students for precisely these questions. They apply shopper session, mission administration and public presentation, explaining technical selections to each engineers and nontechnical stakeholders. By commencement, they’ve already delivered options to actual purchasers, many involving AI, which reveals employers they’ll apply expertise in apply.
Q: What about superior levels?
Bliss: The CRA worries that the U.S. dangers shedding its management place in fields like AI, cybersecurity and quantum computing as a result of fewer home college students are pursuing PhDs. Yet doctoral analysis powers innovation, {industry} progress and nationwide safety. Sustaining that pipeline requires partnerships. We want federal funding, in addition to {industry} help, since most doctoral college students finally go on to corporations the place they create new merchandise, launch sectors and drive competitiveness. Advanced examine additionally equips college students to take on completely new issues that merely can’t be addressed with out deeper coaching.
Maciejewski: For undergraduates, it’s pure to weigh rapid salaries in opposition to years of examine. But superior analysis places you at the frontier, working on issues that may launch startups or reshape industries. At ASU, college students even have alternatives to pursue accelerated master’s degrees, permitting them to deepen their experience with out including many further years of examine. A graduate diploma can open doorways to extra specialised roles and management positions in the workforce. A PhD isn’t for everybody, however for individuals who pursue it, the payoff comes not simply in credentials however in the probability to create completely new alternatives for themselves and others.
The road ahead accommodates each nice challenges and nice alternatives. This is a moment for us to lead.
Nadya Bliss, government director of ASU’s Global Security Initiative
Q: What last recommendation would you give college students?
Bansal: Approach your schooling with agility. Tools and platforms will hold altering, however what lasts are the habits you develop — studying how to be taught, sticking with issues that don’t initially work and collaborating successfully. Those habits will permit you to develop into new alternatives as they seem.
Maciejewski: When I graduated in 2001, the dot-com bubble had simply burst and the job market seemed bleak. What I realized is that cycles come and go, however the individuals who put money into key expertise and keep adaptable are the ones who succeed over time. Don’t measure your future solely by at this time’s headlines. Focus on constructing the type of resilience and experience that can carry you thru shifts in expertise and the economic system alike.
Bliss: What excites me is that completely new lessons of challenges are rising, and they create alternatives for computer scientists at each stage. We’re grappling with the vitality calls for of large-scale computing and the want for low-power architectures. We’re exploring the intersections of AI with quantum computing and biotechnology. These are open issues, and they’re consequential ones. For college students, meaning there may be monumental room to contribute and innovate. The future isn’t about fewer alternatives. It’s about totally different, extra complicated alternatives that require the type of deep coaching school levels can present.